Knowing that wide fluctuations in flow rate and presence of toxic compounds can damage the high efficiency of high-rate anaerobic granular sludge reactors, the use of Principal Component Analysis (PCA) to detect organic and toxic disturbances was tested. As earlier these disturbances are detected, more accurate would be the corrective actions, and less damage will be caused to the microorganisms involved in the process. The PCA determined a latent variable, combining a weighted sum of operational, physiological, and morphological data, which showed high sensitivity to recognize the operational problems occurred when four organic loading disturbances (OLDs) and three toxic shock loads (TSLs) were applied to Expanded Granular Sludge Bed (EGSB) reactors. The high loadings/weights linked with the morphological parameters, specially the aggregates size distribution (>0.1, >1), obtained using quantitative image analysis techniques, demonstrate the usefulness of monitor the anaerobic granular sludge structural changes. The application of PCA chemometric tool to dataset gathering information from all disturbances allowed the differentiation between organic loading and toxic shock disturbances, as well as the main effects caused by each class of disturbance.
Publication Type: Papers